Abstract
A practical electric distribution system is a nonlinear network, which is generally governed by a large number of differential and algebraic equations (DAE). For instance, the ordinary differential equations are defined by the dynamics of the generators (e.g., small-scale hydro generation units) and the loads, as well as distributed generation (DG) units and their controllers. Algebraic equalities are described by the distribution network current balance equations and internal static behaviors of passive devices. In this paper, a rigorous approach is used to convert a semi-explicit DAE system into an explicit ordinary differential equations (ODE) system. In this way, it is possible to apply the robust and well consolidated implicit integration methods to solve the semi-explicit DAE systems as for implicit ODE system. Two applications of the methods are presented. In the first example, the procedure solves the classical Robertson's problem, while in the second case study the dynamic behavior of a simple distribution system with a generator, an induction motor and an admittance load is reported. The results indicate that the proposed procedure is able to reach exactly the same results obtained by applying the classical solution procedure, without any further assumption about the nature of the results obtained.

Abstract
Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute point-spread-function raw intensities. We find that for a 32 × 32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place. © 2014 Optical Society of America.

Abstract

Abstract
Distributed systems rely in communication networks, typically a bus, in order to exchange messages and fulfill their goals. However, message transmission is subject to interferences that ultimately can lead to message corruption. In systems where a high-reliability is sought, error recovery mechanisms can be deployed in order to give the required reliability level, and this can be done in the spatial or temporal domain. In the scope of the FTT paradigm, and applied to the FTT-CAN protocol, the authors have previously presented a time domain recovery method using message retransmissions controlled by a server. In this article we assess the impact of different scheduling policies for the server, presenting a qualitative evaluation of the alternatives, complemented by a simulation study, in order to verify their advantages and weak points.

Abstract
The speed of internationalization of firms has attracted considerable research in the last few decades. However, with regard to a particular type of firm, university spin-offs (USOs), this line of research is still incipient. A majority of the studies on USOs highlights their main features but does not focus on internationalization. Based on the responses from 111 Portuguese USOs, of which 78 are exporters, econometric estimations indicate that: (1) the internationalization speed of USOs is critically dependent on support from technology transfer offices; (2) in line with the “learning advantages of newness” perspective, younger Portuguese USOs reveal higher levels of entrepreneurial spirit and entrepreneurial capabilities, being in a better position to internationalize earlier than older USOs; (3) USOs that operate in microelectronics/robotics internationalize faster and earlier than USOs operating in ICT/software/digital media; and (4) in contrast with the literature on born globals/international new ventures, greater involvement in R&D activities slows down the early internationalization process of USOs.

Abstract
Dysfunctions of the autonomic nervous system in critically ill patients with Acute Brain Injury (ABI) lead to changes in Heart Rate Variability (HRV) which appear to be particularly marked in patients subsequently declared in Brain Death (BD). HRV series are non-stationary, exhibit long memory in the mean and time-varying conditional variance (volatility), characteristics that are well modeled by AutoRegressive Fractionally Integrated Moving Average (ARFIMA) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors. The long memory is estimated by the parameter d of the ARFIMA-GARCH model, whilst the time-varying conditional variance parameters, u and v characterize, respectively, the short-range and the persistence in the conditional variance. In this work, the ARFIMA-GARCH approach is applied to HRV series of 15 pediatric patients with ABI admitted in a pediatric intensive care unit, 5 of which has BD confirmed and 9 patients survived. The long memory and time-varying conditional variance parameters estimated by ARFIMA-GARCH modeling significantly differ between groups and seem able to contribute to characterize disease severity in children with ABI.